Evidence map›Paper›PMID 32164874›Full record

ArticleNeuron2020

Constructing and Forgetting Temporal Context in the Human Cerebral Cortex.

Hsiang-Yun Sherry Chien, Christopher J Honey

Abstract read
In one paragraph

Article in Neuron, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

51 citing papers in PubMed.

  1. The human language processing system straightens natural speech.bioRxiv : the preprint server for biology · 2026
    Article
  2. Narrative "twist" shifts within-individual neural representations of dissociable story features.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Article
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  5. Article
  6. Emergence of a temporal processing gradient from naturalistic inputs and network connectivity.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Article
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  12. Review
  13. Article
  14. Article
  15. Attention-Driven Modulation of Auditory Cortex Activity during Selective Listening in a Multispeaker Setting.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
    Article
  16. Rapid learning of temporal dependencies at multiple timescales.bioRxiv : the preprint server for biology · 2024
    Article
  17. Article
  18. Article
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  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hsiang-Yun Sherry ChienDepartment of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA.
Christopher J HoneyDepartment of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA. Electronic address: chris.honey@jhu.edu.

Funding

Project 5: ComputationalP50MH109429 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI STEPHANIE Ruggiano JONES · 2017 to 2026
$25.3M
Defining Neuronal Circuits and Cellular Processes Underlying Resting fMRI SignalsR01MH111439 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI MILHAM, MICHAEL PETER, SCHROEDER, CHARLES E · 2016 to 2020
$5.1M
Integrating and separating information sequences in the human cerebral cortexR01MH119099 · NIMH · JOHNS HOPKINS UNIVERSITY · PI HONEY, CHRISTOPHER JOHN · 2019 to 2023
$2.5M
NIMH NIH HHS P50 MH109429NIMH NIH HHS R01 MH111439NIMH NIH HHS R01 MH119099
6 · The paper itself

Abstract

How does information from seconds earlier affect neocortical responses to new input? We found that when two groups of participants heard the same sentence in a narrative, preceded by different contexts, the neural responses of each group were initially different but gradually fell into alignment. We observed a hierarchical gradient: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. What computations explain this hierarchical temporal organization? Linear integration models predict that regions that are slower to integrate new information should also be slower to forget old information. However, we found that higher-order regions could rapidly forget prior context. The data from the cortical hierarchy were instead captured by a model in which each region maintains a temporal context representation that is nonlinearly integrated with input at each moment, and this integration is gated by local prediction error.

Indexed as

Models, NeurologicalAdolescentAdultCerebral CortexCognitionEcho-Planar ImagingFemaleHumansMaleMemoryTimeYoung Adultcomputational modelingevent boundaryfMRIhierarchyinter-subject correlationprediction errorsequence processingtemporal contexttemporal integrationtimescales

Identifiers

PMID32164874
PMCPMC7244383

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.